How to use teragron/quantest with llama.cpp:
curl -LsSf https://llama.app/install.sh | sh # Start a local OpenAI-compatible server with a web UI: llama serve -hf teragron/quantest:Q2_K # Run inference directly in the terminal: llama cli -hf teragron/quantest:Q2_K
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf teragron/quantest:Q2_K # Run inference directly in the terminal: llama cli -hf teragron/quantest:Q2_K
# Download pre-built binary from: # https://github.com/ggerganov/llama.cpp/releases # Start a local OpenAI-compatible server with a web UI: ./llama-server -hf teragron/quantest:Q2_K # Run inference directly in the terminal: ./llama-cli -hf teragron/quantest:Q2_K
git clone https://github.com/ggerganov/llama.cpp.git cd llama.cpp cmake -B build cmake --build build -j --target llama-server llama-cli # Start a local OpenAI-compatible server with a web UI: ./build/bin/llama-server -hf teragron/quantest:Q2_K # Run inference directly in the terminal: ./build/bin/llama-cli -hf teragron/quantest:Q2_K
docker model run hf.co/teragron/quantest:Q2_K
How to use teragron/quantest with Ollama:
ollama run hf.co/teragron/quantest:Q2_K
How to use teragron/quantest with Docker Model Runner:
How to use teragron/quantest with Lemonade:
# Download Lemonade from https://lemonade-server.ai/ lemonade pull teragron/quantest:Q2_K
lemonade run user.quantest-Q2_K
lemonade list
